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THE ORIGINAL SOURCE

The Overhang

One Useful Thing ·

A source by Ethan Mollick outlining human advantages—deep knowledge, wide knowledge, taste, and agency—for collaborating with current AI models; explaining how wide knowledge aids prompting by enabling invocation of conceptual frameworks known to LLMs; and noting that domain expertise improves both the quality and quantity of AI output, per Anthropic research.

Ethan Mollick
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At a glance

Key passages3

Attributed passages with the context to verify them. Open the original text to check the source.

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Human advantages with AI

Four personal advantages for working with AI

Original excerpt

In my book, I outline four particular personal advantages that matter a lot if you want to use AI in unique and enhancing ways: deep knowledge, wide knowledge, taste, and agency.
Ethan Mollick·
Context

That is why I think we will need to focus on the individual traits we have that remain useful even as AI abilities improve. You are not trying to compete with AI in producing outputs, that is a losing game. Instead, you want to use your human advantages as basis of working with AI to do things that neither of you could do alone.

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Expertise and AI output quality

Deep knowledge improves AI results

Original excerpt

And recent work from Anthropic suggests that expertise also shapes the quality of what AI gives back . Experts not only get better work out of AI, they get more work out of it.
Ethan Mollick·
Context

The first two advantages come from what you know. Deep knowledge is the expertise that comes from understanding a field or subject so well that you build intuition around it to quickly and accurately make decisions. It is how an experienced accountant can glance at a spreadsheet and know something is wrong, or how a golf pro can watch a swing and instantly understand the mistake the golfer is making. It is also why I could tell within seconds that the first trailer was more ominous than the book actually is. Deep knowledge is the realm of the specialist, and it is the only way to truly understand the shape of the Jagged Frontier, because only experts can understand the patterns of where AI succeeds or fails, at least in their area of expertise. It also helps you adapt to change because deep knowledge makes it easier to switch from being someone who does the work to someone who manages it.

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interdisciplinary literacy

Wide knowledge enables effective prompting

Original excerpt

The training data for LLMs is a large swath of humanity’s vast output. The AI has learned something of design thinking and Bayesian reasoning and the Toyota Production System and Rogerian therapy and Marxist literary criticism. But AI tends not to volunteer any of these patterns unless you know to ask.
Ethan Mollick·
Context

But you don’t just need deep knowledge, you also want wide knowledge.

Source & methodology

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